06/04 2025

workflowr

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Last updated: 2025-08-07

Checks: 6 1

Knit directory: Collaborations/

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File	Version	Author	Date	Message
Rmd	3614e56	han	2025-08-07	8/7/2025
html	3614e56	han	2025-08-07	8/7/2025
Rmd	10206de	han	2025-08-06	8/6/202
html	10206de	han	2025-08-06	8/6/202
Rmd	77c218e	han	2025-08-06	8/6/2025
html	77c218e	han	2025-08-06	8/6/2025
Rmd	5d069dc	han	2025-08-06	8/6/2025
html	5d069dc	han	2025-08-06	8/6/2025
Rmd	d62c51e	han	2025-07-28	7/28/2025
html	d62c51e	han	2025-07-28	7/28/2025
Rmd	48567d2	han	2025-07-28	7/28/2025
html	48567d2	han	2025-07-28	7/28/2025
Rmd	e15351d	han	2025-07-28	7/28/2025
html	e15351d	han	2025-07-28	7/28/2025
Rmd	6d54c64	han	2025-06-05	6/5/2025
html	6d54c64	han	2025-06-05	6/5/2025

---

data_raw=multiplesheets((file.path(root, "..\\2025\\202506\\Shikha\\Dr. Gupta Endo Data.xlsx")))
endo_cases=data_raw$EndoCases
endo_cases=endo_cases %>% mutate(tooth=paste0(endo_cases$Patient, ":", endo_cases$Site))

post_endo_tx=data_raw$`Post Endo TX`
post_endo_tx=post_endo_tx %>% mutate(tooth=paste0(post_endo_tx$Patient, ":", post_endo_tx$Site))

step 1: root canal

# Create a data frame
root_canal_codes <- data.frame(
  Code = c("D3310", "D3320", "D3330"),
  Description = c(
    "anterior RCT",
    "bicuspid RCT",
    "molar RCT"
  )
)

root_canal_codes%>%
datatable(extensions = 'Buttons',
          caption = "root canal Codes", 
            options = list(dom = 'Blfrtip',
                           buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
                           lengthMenu = list(c(10,25,50,-1),
                                             c(10,25,50,"All"))))

endo_cases_with_root_canal=endo_cases %>% filter(Procedure %in% root_canal_codes$Code)%>%
  group_by(tooth) %>%
  arrange(Date) %>%
  slice_tail(n = 1) %>%  # Keeps the last root canal date
  ungroup()

endo_cases_with_root_canal$Date=as.Date(endo_cases_with_root_canal$Date)
endo_cases_with_root_canal$Birth=as.Date(endo_cases_with_root_canal$Birth)

endo_cases_with_root_canal %>%
datatable(extensions = 'Buttons',
          caption = "", 
            options = list(dom = 'Blfrtip',
                           buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
                           lengthMenu = list(c(10,25,50,-1),
                                             c(10,25,50,"All"))))

• only keep the latest root canal if the tooth has multiple root canals.

# Count the number of each Procedure
procedure_counts <- endo_cases_with_root_canal %>%dplyr::count(Procedure)

# Bar plot
ggplot(procedure_counts, aes(x = Procedure, y = n, fill=Procedure)) +
  geom_bar(stat = "identity") +
  geom_text(aes(label = n), vjust = -0.5, size = 4) +
  labs(
    title = "",
    x = "Procedure Code",
    y = "Count"
  ) +
  theme_minimal() +
  theme(
    text = element_text(size = 14),
    plot.title = element_text(hjust = 0.5, face = "bold")
  )

Past versions of unnamed-chunk-5-1.png

Version	Author	Date
3614e56	han	2025-08-07
5d069dc	han	2025-08-06

step 2: initial treatment

# Create a data frame of Final Restoration codes
final_restoration_codes <- data.frame(
  Code = c(
    "D2390", "D2391", "D2392", "D2393", "D2394",
    "D2650", "D2651", "D2652", "D2662", "D2663", "D2664",
    "D2710", "D2712", "D2720", "D2721", "D2722",
    "D2910", "D2915", "D2920", "D2932", "D2933",
    "D2940", "D2949", "D2950", "D2951", "D2952", "D2954",
    "D6068", "D6069", "D6070", "D6071", "D6072", "D6073", "D6074",
    "D6545", "D6548", "D6611",
    "D6710", "D6720", "D6721", "D6722",
    "D6740", "D6750", "D6780", "D6790", "D6793",
    "D6930", "D6971"
  ),
  Description = c(
    "Resin-based comp crown, ant.",
    "Resin-based comp - 1 surface, posterior",
    "Resin-based comp - 2 surfaces, posterior",
    "Resin-based comp - 3 surfaces, posterior",
    "Resin-based comp - 4+ surfaces, posterior",
    "Inlay - resin - 1 surface",
    "Inlay - resin - 2 surfaces",
    "Inlay - resin - 3 or more",
    "Onlay - resin - 2 surfaces",
    "Onlay - resin - 3 surfaces",
    "Onlay - resin - 4 or more",
    "Resin crown - laboratory",
    "Crown - 3/4 resin-based comp",
    "Resin crown - high noble metal",
    "Resin crown - predominately base metal",
    "Resin crown - noble metal",
    "Recement/re-bond inlay/onlay",
    "Recement cast or prefab post",
    "Recement/re-bond crown",
    "Prefabricated resin crown",
    "Prefab stainless steel crown w/ resin window",
    "Protective restoration",
    "Restorative foundation/indirect restoration",
    "Core buildup - including pins",
    "Pin retention - per tooth",
    "Post & core, indirect fabrication",
    "Prefab post and core",
    "Abutment-retainer, porcelain/ceramic FPD",
    "Abutment-ret., PFM FPD, high noble",
    "Abutment-ret., PFM FPD, base metal",
    "Abutment-ret., PFM FPD, noble metal",
    "Abut-ret., cast metal, high noble",
    "Abut-ret., cast metal, base metal",
    "Abut-ret., cast metal, noble metal",
    "Retainer, metal, resin-bonded FPD",
    "Retainer, porcelain/ceramic, bonded FPD",
    "Retainer onlay, high noble metal, 3+ surfaces",
    "Crown - indirect resin-based",
    "Crown - resin, high noble metal",
    "Crown - resin, predominately base metal",
    "Crown - resin, noble metal",
    "Retainer crown - porcelain/ceramic",
    "Retainer crown - porcelain fused to high noble metal",
    "Retainer crown - 3/4 cast, high noble metal",
    "Retainer crown - full cast, high noble metal",
    "Provisional retainer crown",
    "Recement/re-bond FPD",
    "Cast post - part of FPD retainer"
  )
)

post_endo_tx_with_final_restoration_codes=post_endo_tx %>% filter(Procedure %in% final_restoration_codes$Code ) %>% filter(`Endo Check`=="Yes")

final_restoration_codes%>%
datatable(extensions = 'Buttons',
          caption = "restoration codes", 
            options = list(dom = 'Blfrtip',
                           buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
                           lengthMenu = list(c(10,25,50,-1),
                                             c(10,25,50,"All"))))

time period between root canal and inital treatment

library(dplyr)
library(DT)

# Ensure Date columns are Date type
endo_cases_with_root_canal$Date <- as.Date(endo_cases_with_root_canal$Date)
post_endo_tx_with_final_restoration_codes$Date <- as.Date(post_endo_tx_with_final_restoration_codes$Date)

# Step 1: Rename columns for clarity
endo_root <- endo_cases_with_root_canal %>%
  rename(
    root_canal_date = Date,
    root_canal_procedure = Procedure
  )

restoration <- post_endo_tx_with_final_restoration_codes %>%
  rename(
    restoration_date = Date,
    restoration_procedure = Procedure
  )

# Step 2: Perform inner join on tooth, retaining all necessary columns explicitly
joined <- endo_root %>%
  select(Patient, tooth, root_canal_date, root_canal_procedure) %>%
  inner_join(restoration %>% select(tooth, restoration_date, restoration_procedure),
             by = "tooth")

# Step 3: Filter restorations that occurred *after* root canal
after_root_canal <- joined %>%
  filter(restoration_date > root_canal_date)

# Step 4: Group by root canal event (Patient + tooth + date) and get earliest restoration
first_restoration <- after_root_canal %>%
  group_by(Patient, tooth, root_canal_date) %>%
  arrange(restoration_date) %>%
  slice(1) %>%
  ungroup()

# Step 5: Calculate time difference and select output columns
endo_with_tx_time <- first_restoration %>%
  mutate(
    time_between_days = as.numeric(restoration_date - root_canal_date)
  ) %>%
  select(
    Patient,
    tooth,
    root_canal_date,
    root_canal_procedure,
    first_restoration_date = restoration_date,
    first_restoration_procedure = restoration_procedure,
    time_between_days
  )

endo_with_tx_time %>%
  datatable(
    extensions = 'Buttons',
    options = list(
      dom = 'Blfrtip',
      buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
      lengthMenu = list(c(10, 25, 50, -1), c(10, 25, 50, "All"))
    )
  )

• if a tooth has multiple restorations after root canal, keep the earliest one only.

library(dplyr)
library(lubridate)

# Ensure Date columns are Date type
endo_cases_with_root_canal$Date <- as.Date(endo_cases_with_root_canal$Date)
post_endo_tx_with_final_restoration_codes$Date <- as.Date(post_endo_tx_with_final_restoration_codes$Date)

# Rename for clarity
endo <- endo_cases_with_root_canal %>%
  rename(endo_date = Date,
         endo_procedure = Procedure)

resto <- post_endo_tx_with_final_restoration_codes %>%
  rename(restoration_date = Date,
         restoration_procedure = Procedure)

# Perform many-to-many join by "tooth"
combined <- inner_join(endo, resto, by = "tooth") %>%
  # Optional: restrict to matching Patient as well
  filter(Patient.x == Patient.y) %>%
  mutate(time_between_days = as.numeric(restoration_date - endo_date)) %>%
  select(
    Patient = Patient.x,
    tooth,
    endo_date,
    endo_procedure,
    restoration_date,
    restoration_procedure,
    time_between_days
  ) %>%
  arrange(Patient, tooth, endo_date, restoration_date)

# View results

combined %>%
  datatable(
    extensions = 'Buttons',
    caption = "",
    options = list(
      dom = 'Blfrtip',
      buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
      lengthMenu = list(c(10, 25, 50, -1), c(10, 25, 50, "All"))
    )
  )

step 3: post treatment

# Create a data frame
failure_codes <- data.frame(
  Code = c("D3346", "D3347", "D3348", "D3421", "D3425", "D3410", "D3426",
           "D3430", "D3450", "D3470", "D3505", "D3920", "D7140", "D7210"),
  Description = c(
    "Anterior-retreat prev. rt. canal",
    "Bicuspid retreat prev. rt. canal",
    "Molar retreat prev. rt. canal",
    "Apicoectomy - bicuspid (1st root)",
    "Apicoectomy - molar (1st root)",
    "Apicoectomy - anterior",
    "Apicoectomy - additional roots",
    "Retrograde filling - per root",
    "Root amputation - per root",
    "Intentional reimplantation",
    "Surgical exposure of root surface w/o apicoectomy",
    "Hemisection, incl. root removal",
    "Extraction",
    "Surgical removal of erupted tooth"
  )
)


failure_codes%>%
datatable(extensions = 'Buttons',
          caption = "Extraction /failure codes", 
            options = list(dom = 'Blfrtip',
                           buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
                           lengthMenu = list(c(10,25,50,-1),
                                             c(10,25,50,"All"))))

# Step 1: Define the failure-related procedure codes
failure_codes <- c(
  "D3346", "D3347", "D3348", "D3421", "D3425",
  "D3410", "D3426", "D3430", "D3450", "D3470",
  "D3505", "D3920", "D7140", "D7210"
)

# Step 2: Extract only failure events from all procedures
# all_procedures must include: Patient, tooth, Date, Procedure
failure_events <- post_endo_tx %>% filter(`Endo Check`=="Yes") %>% 
  filter(Procedure %in% failure_codes) %>%
  rename(failure_date = Date, failure_code = Procedure) %>%
  select(Patient, tooth, failure_date, failure_code)

failure_events$failure_date=as.Date(failure_events$failure_date)

# Step 3: Join with endo_with_tx_time and filter for valid failures (after restoration)
endo_with_failure <- endo_with_tx_time %>%
  left_join(failure_events, by = c("Patient", "tooth")) %>%
  filter(is.na(failure_date) | failure_date >= first_restoration_date) %>%  # allow NA for no failure
  group_by(Patient, tooth, root_canal_date) %>%
  arrange(failure_date) %>%
  slice(1) %>%  # earliest failure (or NA)
  ungroup() %>%
  mutate(
    survival_days = as.numeric(failure_date - first_restoration_date),
    survival_weeks = round(survival_days / 7,2), 
    survival_months = round(survival_days / 30.44,2), 
    survival_years = round(survival_days / 365.25, 2)
  )

endo_with_failure%>%
datatable(extensions = 'Buttons',
          caption = "", 
            options = list(dom = 'Blfrtip',
                           buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
                           lengthMenu = list(c(10,25,50,-1),
                                             c(10,25,50,"All"))))

survival analysis

# Load required libraries
library(survival)
library(survminer)

# Step 1: Prepare the data
survival_data <- endo_with_failure %>%
  mutate(
    # Event flag: 1 = failed, 0 = censored
    event = ifelse(is.na(failure_date), 0, 1),
    # Time to event in days
    survival_days = as.numeric(failure_date - first_restoration_date)
  )

# Step 2: Create a Surv object
surv_object <- Surv(time = survival_data$survival_days, event = survival_data$event)

# Step 3: Fit Kaplan-Meier survival model
km_fit <- survfit(surv_object ~ 1)

# Step 4: Plot Kaplan-Meier survival curve
ggsurvplot(
  km_fit,
  data = survival_data,  # ✅ This solves the error
  conf.int = TRUE,
  xlab = "Days since first restoration",
  ylab = "Tooth survival probability",
  title = "Kaplan-Meier Survival Curve of Root Canal Treated Teeth",
  surv.median.line = "hv",
  risk.table = TRUE,
  risk.table.height = 0.25
)

Past versions of unnamed-chunk-11-1.png

Version	Author	Date
3614e56	han	2025-08-07
5d069dc	han	2025-08-06

Session information

sessionInfo()

R version 4.3.2 (2023-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 11 x64 (build 26100)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/Chicago
tzcode source: internal

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] survminer_0.5.0     survival_3.8-3      VennDiagram_1.7.3  
 [4] futile.logger_1.4.3 condsurv_1.0.0      devtools_2.4.5     
 [7] usethis_3.1.0       tidycmprsk_1.1.0    gtsummary_2.0.4    
[10] ggsurvfit_1.1.0     irr_0.84.1          lpSolve_5.6.23     
[13] readxl_1.4.3        cowplot_1.1.3       matrixStats_1.5.0  
[16] gridExtra_2.3       DT_0.33             rstatix_0.7.2      
[19] ggpubr_0.6.0        kableExtra_1.4.0    lubridate_1.9.4    
[22] forcats_1.0.0       stringr_1.5.1       dplyr_1.1.4        
[25] purrr_1.0.2         readr_2.1.4         tidyr_1.3.1        
[28] tibble_3.2.1        ggplot2_3.5.1       tidyverse_2.0.0    
[31] rprojroot_2.0.4    

loaded via a namespace (and not attached):
 [1] formatR_1.14         remotes_2.5.0        rlang_1.1.2         
 [4] magrittr_2.0.3       git2r_0.35.0         compiler_4.3.2      
 [7] systemfonts_1.2.1    vctrs_0.6.5          profvis_0.4.0       
[10] pkgconfig_2.0.3      fastmap_1.2.0        backports_1.5.0     
[13] ellipsis_0.3.2       labeling_0.4.3       KMsurv_0.1-5        
[16] promises_1.3.2       rmarkdown_2.29       markdown_1.13       
[19] sessioninfo_1.2.2    tzdb_0.4.0           xfun_0.50.6         
[22] cachem_1.1.0         jsonlite_1.8.9       later_1.4.1         
[25] broom_1.0.7          R6_2.5.1             bslib_0.9.0         
[28] stringi_1.8.3        car_3.1-3            pkgload_1.4.0       
[31] jquerylib_0.1.4      cellranger_1.1.0     Rcpp_1.0.11         
[34] knitr_1.49           zoo_1.8-14           httpuv_1.6.15       
[37] Matrix_1.6-1.1       splines_4.3.2        timechange_0.3.0    
[40] tidyselect_1.2.1     rstudioapi_0.17.1    abind_1.4-8         
[43] yaml_2.3.8           ggtext_0.1.2         miniUI_0.1.1.1      
[46] pkgbuild_1.4.6       lattice_0.21-9       shiny_1.10.0        
[49] withr_3.0.2          evaluate_1.0.3       lambda.r_1.2.4      
[52] urlchecker_1.0.1     xml2_1.3.6           survMisc_0.5.6      
[55] pillar_1.10.1        carData_3.0-5        whisker_0.4.1       
[58] generics_0.1.3       hms_1.1.3            commonmark_1.9.2    
[61] munsell_0.5.1        scales_1.3.0         xtable_1.8-4        
[64] glue_1.8.0           tools_4.3.2          data.table_1.16.4   
[67] ggsignif_0.6.4       fs_1.6.5             crosstalk_1.2.1     
[70] colorspace_2.1-0     Formula_1.2-5        cli_3.6.2           
[73] km.ci_0.5-6          workflowr_1.7.1      futile.options_1.0.1
[76] viridisLite_0.4.2    svglite_2.1.3        gtable_0.3.6        
[79] sass_0.4.9           digest_0.6.33        farver_2.1.2        
[82] htmlwidgets_1.6.4    memoise_2.0.1        htmltools_0.5.8.1   
[85] lifecycle_1.0.4      mime_0.12            gridtext_0.1.5